Reverberation reduction solutions are known in the field of audio signal processing. Many conventional approaches are not suitable for use in real-time applications. For example, a reverberation reduction solution may require a long buffer of data to compensate for the effect of reverberation or to estimate an inverse filter of the Room Impulse Responses (RIR). Approaches that are suitable for real-time applications do not perform reasonably well in high reverberation and especially high non-stationary environments. In addition, such solutions require a large amount of memory and it is not computationally efficient for many low power devices.
One conventional solution is based on weighted prediction error (WPE), which assumes an autoregressive model of the reverberation process, i.e., it is assumed that the reverberant component at a certain time can be predicted from previous samples of reverberant microphone signals. The desired signal can be estimated as the prediction error of the model. A fixed delay is introduced to avoid distortion of the short-time correlation of the speech signal. This algorithm is not suitable for real-time processing and does not explicitly model the input signal in noisy conditions. Also, the WPE method, has high complexity and is not Online multiple-input multiple-output (MIMO) solution. The WPE approach has been extended for MIMO and generalized for use in noisy condition. However, such modifications are not suitable for time-varying environments. Further modifications for time-varying environments have been proposed, which include both WPE for linear filtering and an optimum combination of the beamforming and a Wiener-filtering-based nonlinear filtering. However, such proposals are still not real-time and are not suitable for use in low power devices because of its high complexity.
Generally, conventional methods have limitations in complexity and practicality for use in on-line and real-time applications. Unlike batch processing, a real-time or online processing is used in industry for many practical applications. There is therefore a need for improved systems and methods for online and real-time dereverberation.